Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

Traditional Chinese medicine(TCM)is an ancient medical system distinctive and effective in treating cancer,depression,coronavirus disease 2019(COVID-19),and other diseases.However,the relatively abstract diagnostic methods of TCM lack objective measurement,and the complex mechanisms of action are difficult to comprehend,which hinders the application and internationalization of TCM.Recently,while breakthroughs have been made in utilizing methods such as network pharmacology and virtual screening for TCM research,the rise of machine learning(ML)has significantly enhanced their inte-gration with TCM.This article introduces representative methodological cases in quality control,mechanism research,diagnosis,and treatment processes of TCM,revealing the potential applications of ML technology in TCM.Furthermore,the challenges faced by ML in TCM applications are summarized,and future directions are discussed.

Alzheimer's disease(AD)is an age-related neurodegenerative disease with an increasing incidence worldwide.A large number of studies have shown that the incidence rates of hearing loss is high in patients with mild cognitive impairment and Alzheimer's disease,and may be a risk factor for the occurrence and development of cognitive impairment.There is an interaction between the two,but the causal mechanism is still unclear.Early screening and management of hearing impairment may play an important role in the early diagnosis,symptom im-provement and disease progression of Alzheimer's disease.This paper reviews relevant clinical and basic research to discuss the correlation between hearing loss and Alzheimer's disease,and the possible causal mechanism between them.

Hair follicles are skin appendages with a complex structure and periodical self-renewal ability. The hair follicle cycle includes the anagen phase, catagen phase and telogen phase, and its orderly renewal is important to maintain hair growth. It is currently believed that Wnt, bone morphogenetic protein, and Notch signaling pathways are involved in regulating the hair follicle cycle. As research progresses, various regulatory mechanisms based on these signaling pathways have been gradually revealed, such as growth factors, non-coding RNAs, immune responses, etc. This review elaborates on the above molecular mechanisms and regulatory modalities, aiming to promote better understandingn of regulatory mechanisms underlying the hair follicle cycle and provide a theoretical reference for expanding treatment options for hair loss.

Multi-family therapy (MFT), as an extension of traditional family therapy, refers to a treatment method in which family members from multiple families participate at the same time. Although its application in severe mental disorders such as schizophrenia is mature, its potential in a wider field and its localization pathway need to be systematically discussed. This paper aims to summarize the development, treatment settings and requirements of the early classic model of MFT, analyze its core mechanism, focus on summarizing the emerging application model variants and effectiveness of MFT in medical care (schizophrenia, eating disorders), school education (refusing to intervene in school) and social work (treating ADHD children, traumatized families, etc.), and comprehensively explore the research methods of effect evaluation.However, there are still some limitations in the current researches, such as lax evaluation, unclear specific action pathway, family vulnerability and lack of cross-cultural adaptability research. Finally, the future development direction is prospected to provide reference for promoting the application practice of MFT.

Objective This study aims to evaluate the therapeutic efficacy of Compound Fufangteng Mixture(CFM)on myocardial fibrosis(MF)and explore its action targets and mechanisms through a combination of animal pharmacodynamics,cell biology,and network pharmacology approaches.Methods Thirty-five male C57BL/6J mice were divided into the normal group,model group,CFM low-dose(0.72 g/kg)group,CFM high-dose(1.44 g/kg)group,and sacubitril valsartan sodium group(20 mg/kg)based on random number table,with 7 mice in each group.Except for the normal group,the mice in the other groups were subcutaneously injected with isoproterenol(20 mg/kg)at multiple points once daily for 21 consecutive days to establish the MF model.The CFM groups were pre-administered by gavage 3 days before modeling,the sacubitril valsartan sodium group was administered starting from the day of modeling,and the normal group and model group were given an equal volume of distilled water.The active ingredients in CFM were analyzed using ultra-performance liquid chromatography(UPLC).On days 7,14,and 21 of modeling,the left ventricular ejection fraction(LVEF),left ventricular fractional shortening(LVFS),left ventricular end-diastolic diameter(LVIDd),and left ventricular end-systolic diameter(LVIDs)of mice were detected by ultrasound.The degree of myocardial fibrosis in mice was assessed by Masson staining.The levels of transforming growth factor-β1(TGF-β1),α-smooth muscle actin(α-SMA),type I collagen(COL I),and type Ⅲcollagen(COL Ⅲ)in the myocardial tissue of mice were detected by enzyme-linked immunosorbent assay(ELISA).The average fluorescence intensity of α-SMA in myocardial tissue was detected by immunofluorescence.In addition,by integrating Cellular Thermal Shift Assay(CETSA),QE proteomic analysis,and network pharmacology techniques,we systematically explored the potential core targets and mechanisms of action by which CFM improves MF,and validated these findings using western blotting analysis.Results Main eight chemical components were identified from CFM.Compared with the normal group,the model group exhibited a decrease in LVEF and LVFS,an increase in LVIDd and LVIDs,a higher heart weight to tibia length ratio,and an increased collagen volume fraction(P<0.05),along with aggravated MF.Concurrently,the myocardial tissue showed elevated levels of TGF-β1,α-SMA,COL I,and COL Ⅲ(P<0.05),with enhanced α-SMA fluorescence signal intensity.In comparison to the model group,all groups of CFM and the sacubitril valsartan sodium group demonstrated an increase in LVEF and LVFS,and a decrease in LVIDd,LVIDs,and the heart weight to tibia length ratio(P<0.05).Simultaneously,the collagen volume fraction decreased,and the levels of TGF-β1,α-SMA,COL I,and COL Ⅲ in myocardial tissue were down-regulated(P<0.05).The degree of MF was reduced,and the fluorescence signal intensity of α-SMA expression was weakened.Furthermore,the combined analysis of CETSA,QE proteomics,and network pharmacology revealed that heat shock protein A family member 8(HSPA8)may be a potential core target for CFM in ameliorating MF.CETSA-western blotting analysis further confirmed that CFM could enhance the thermal stability of HSPA8 protein and down-regulate the relative expression level of HSPA8 protein in mouse myocardial tissue(P<0.05).Conclusion CFM can ameliorate isoproterenol-induced cardiac dysfunction in mice,reduce collagen deposition,and reverse the pathological progression of MF.The underlying mechanism may be associated with the regulation of HSPA8.

Objective:To observe the effectiveness of extracorporeal counterpulsation therapy in patients with heart failure in ischaemic cardiomyopathy.Methods:A total of 112 patients with ischemic cardiomyopathy and heart failure admitted to the Second Affiliated Hospital of Xingtai Medical College from August 2020 to June 2023 were prospectively selected and divided into two groups by random number table method. The control group was treated with conventional drugs and conventional cardiac rehabilitation program, and the observation group was combined with external counterbeating therapy on the basis of the control group. The levels of N-terminal B-type brain natriuretic peptide (NTproBNP), soluble growth stimulation-expression gene-2 protein (sST2), neutrophil gelatinase-associated lipid carrier protein (NGAL), galactin-3 (Gal-3), cardiopulmonary exercise test (CPET) parameters and cardiac ultrasound indexes were compared between the two groups before and after treatment. The curative effect and the rate of re-hospitalization within 6 months were compared between the two groups.Results:After treatment, the levels of NTproBNP, sST2, NGAL and Gal-3 in the observation group were lower than those in the control group: (1941.36 ± 312.59) ng/L vs. (2674.22 ± 404.64) ng/L, (44.78 ± 3.97) ng/L vs. (52.45 ± 4.13) ng/L, (22.63 ± 3.65) μg/L vs. (26.41 ± 3.77) μg/L, (4.63 ± 1.29) ng/L vs. (6.11 ± 1.78) ng/L, there were statistical differences ( P<0.05); the maximum kilogram oxygen uptake (VO 2max/kg), maximum kilogram oxygen uptake as a percentage of predicted value (VO 2max/kg%pred), maximum minute ventilation as a percentage of predicted value (VEmax%pred) in the observation group were higher than those in the control group: (22.41 ± 2.23) ml/(min·kg) vs. (21.35 ± 2.09) ml/(min·kg), (83.79 ± 11.04)% vs. (78.74 ± 10.14)%, (88.95 ± 12.74)% vs. (75.45 ± 11.14)%, there were statistical differences ( P<0.05 or <0.01); the left ventricular ejection fraction (LVEF) in the observation group was higher than that in the control group and the left ventricular posterior wall thickness (LVPWT) and left ventricular posterior wall end-systolic thickness (PWS) were lower than those in the control group: (50.12 ± 3.87)% vs. (48.63 ± 3.74)%, (8.77 ± 1.58) mm vs. (9.63 ± 1.97) mm, (9.34 ± 1.54) mm vs. (10.14 ± 1.79) mm, there were statistical differences ( P<0.05). There was no statistical difference in the total effective rate between the two groups ( P>0.05). The patient readmission rate within 6 months of follow-up in the observation group was lower than that in the control group: 5.45%(3/55) vs. 20.00%(11/55), there was statistical difference( χ2 = 5.24, P<0.05). Conclusions:Extracorporeal counterpulsation therapy for the treatment of heart failure in ischaemic cardiomyopathy can improve the cardiorespiratory function, reduce the expression of NTproBNP, sST2, NGAL and Gal-3, and decrease the patient readmission rate.